Cooperative distributed sequential spectrum sensing

We consider cooperative spectrum sensing for cognitive radios. We develop an energy efficient detector with low detection delay using sequential hypothesis testing. Sequential Probability Ratio Test (SPRT) is used at both the local nodes and the fusion center. We also analyse the performance of this algorithm and compare with the simulations. Modelling uncertainties in the distribution parameters are considered. Slow fading with and without perfect channel state information at the cognitive radios is taken into account.

A novel algorithm for cooperative distributed sequential spectrum sensing in Cognitive Radio

This paper considers cooperative spectrum sensing in Cognitive Radios. In our previous work we have developed DualSPRT, a distributed algorithm for cooperative spectrum sensing using Sequential Probability Ratio Test (SPRT) at the Cognitive Radios as well as at the fusion center. This algorithm works well, but is not optimal. In this paper we propose an improved algorithm- SPRT-CSPRT, which is motivated from Cumulative Sum Procedures (CUSUM). We analyse it theoretically. We also modify this algorithm to handle uncertainties in SNR's and fading.

SpecNet: Spectrum Sensing Sans Frontieres

While the under-utilization of licensed spectrum based on measurement studies conducted in a few developed countries has spurred lots of interest in opportunistic spectrum access, there exists no infrastructure today for measuring real-time spectrum occupancy across vast geographical regions. In this paper, we present the design and implementation of SpecNet, a first-of-its-kind platform that allows spectrum analyzers around the world to be networked and efficiently used in a coordinated manner for spectrum measurement as well as implementa- tion and evaluation of distributed sensing applications. We demonstrate the value of SpecNet through three applications: 1) remote spectrum measurement, 2) primary transmitter coverage estimation and 3) Spectrum-Cop that quickly identifies and localizes transmitters in a frequency range and geographic region of interest.

Cooperative distributed sequential spectrum sensing

We consider cooperative spectrum sensing for cognitive radios. We develop an energy efficient detector with low detection delay using sequential hypothesis testing. Sequential Probability Ratio Test (SPRT) is used at both the local nodes and the fusion center. We also analyse the performance of this algorithm and compare with the simulations. Modelling uncertainties in the distribution parameters are considered. Slow fading with and without perfect channel state information at the cognitive radios is taken into account.

Frequency detection from multiplexed compressed sensing of noisy signals

Signal acquisition under a compressed sensing scheme offers the possibility of acquisition and reconstruction of signals sparse on some basis incoherent with measurement kernel with sub-Nyquist number of measurements. In particular when the sole objective of the acquisition is the detection of the frequency of a signal rather than exact reconstruction, then an undersampling framework like CS is able to perform the task. In this paper we explore the possibility of acquisition and detection of frequency of multiple analog signals, heavily corrupted with additive white Gaussian noise. We improvise upon the MOSAICS architecture proposed by us in our previous work to include a wider class of signals having non-integral frequency components. This makes it possible to perform multiplexed compressed sensing for general frequency sparse signals.

Random forest algorithm with derived geographical layers for improved classification of remote sensing data

Effective conservation and management of natural resources requires up-to-date information of the land cover (LC) types and their dynamics. The LC dynamics are being captured using multi-resolution remote sensing (RS) data with appropriate classification strategies. RS data with important environmental layers (either remotely acquired or derived from ground measurements) would however be more effective in addressing LC dynamics and associated changes. These ancillary layers provide additional information for delineating LC classes' decision boundaries compared to the conventional classification techniques. This communication ascertains the possibility of improved classification accuracy of RS data with ancillary and derived geographical layers such as vegetation index, temperature, digital elevation model (DEM), aspect, slope and texture. This has been implemented in three terrains of varying topography. The study would help in the selection of appropriate ancillary data depending on the terrain for better classified information.

Abrin Immunotoxin: Targeted Cytotoxicity and Intracellular Trafficking Pathway

Background: Immunotherapy is fast emerging as one of the leading modes of treatment of cancer, in combination with chemotherapy and radiation. Use of immunotoxins, proteins bearing a cell-surface receptor-specific antibody conjugated to a toxin, enhances the efficacy of cancer treatment. The toxin Abrin, isolated from the Abrus precatorius plant, is a type II ribosome inactivating protein, has a catalytic efficiency higher than any other toxin belonging to this class of proteins but has not been exploited much for use in targeted therapy. Methods: Protein synthesis assay using (3)H] L-leucine incorporation; construction and purification of immunotoxin; study of cell death using flow cytometry; confocal scanning microscopy and sub-cellular fractionation with immunoblot analysis of localization of proteins. Results: We used the recombinant A chain of abrin to conjugate to antibodies raised against the human gonadotropin releasing hormone receptor. The conjugate inhibited protein synthesis and also induced cell death specifically in cells expressing the receptor. The conjugate exhibited differences in the kinetics of inhibition of protein synthesis, in comparison to abrin, and this was attributed to differences in internalization and trafficking of the conjugate within the cells. Moreover, observations of sequestration of the A chain into the nucleus of cells treated with abrin but not in cells treated with the conjugate reveal a novel pathway for the movement of the conjugate in the cells. Conclusions: This is one of the first reports on nuclear localization of abrin, a type II RIP. The immunotoxin mAb F1G4-rABRa-A, generated in our laboratory, inhibits protein synthesis specifically on cells expressing the gonadotropin releasing hormone receptor and the pathway of internalization of the protein is distinct from that seen for abrin.

Combination of single walled carbon nanotubes/graphene oxide with paclitaxel: a reactive oxygen species mediated synergism for treatment of lung cancer

Heterogeneity in tumors has led to the development of combination therapies that enable enhanced cell death. Previously explored combination therapies mostly involved the use of bioactive molecules. In this work, we explored a non-conventional strategy of using carbon nanostructures (CNs) single walled carbon nanotube (SWNT) and graphene oxide (GO)] for potentiating the efficacy of a bioactive molecule paclitaxel (Tx)] for the treatment of lung cancer. The results demonstrated enhanced cell death following combination treatment of SWNT/GO and Tx indicating a synergistic effect. In addition, synergism was abrogated in the presence of an anti-oxidant, N-acetyl cysteine (NAC), and was therefore shown to be reactive oxygen species (ROS) dependent. It was further demonstrated using bromodeoxyuridine (BrdU) incorporation assay that treatment with CNs was associated with enhanced mitogen associated protein kinase (MAPK) activation that was ROS mediated. Hence, these results for the first time demonstrated the potential of SWNT/GO as co-therapeutic agents with Tx for the treatment of lung cancer.

Evidence of collective relaxation behavior in the reentrant phase of oxygen-rich LaMnO3

The reentrant low temperature phase of the perovskite manganite LaMnO3+delta (delta=0.22) has been investigated with ac susceptibility and dc magnetization studies. A critical examination of the memory effects in ac susceptibility leads us to the conclusion that the slow dynamics in the system is a consequence of collective relaxation processes resulting from interactions between ferromagnetic clusters, whose presence was indicated in earlier studies. Here, we postulate that the collective behavior is due to the existence of long-range (dipolar) interactions between the large ferromagnetic `superspins'. This is also confirmed by an abnormally large microscopic spin-flip time (similar to 10(-9) s) compared to a canonical spin glass. (C) 2013 Elsevier B.V. All rights reserved.

Analysis of integrated optofluidic lab-on-a-chip sensor based on refractive index and absorbance sensing

The analysis of a fully integrated optofluidic lab-on-a-chip sensor is presented in this paper. This device is comprised of collinear input and output waveguides that are separated by a microfluidic channel. When light is passed through the analyte contained in the fluidic gap, optical power loss occurs owing to absorption of light. Apart from absorption, a mode-mismatch between the input and output waveguides occurs when the light propagates through the fluidic gap. The degree of mode-mismatch and quantum of optical power loss due to absorption of light by the fluid form the basis of our analysis. This sensor can detect changes in refractive index and changes in concentration of species contained in the analyte. The sensitivity to detect minute changes depends on many parameters. The parameters that influence the sensitivity of the sensor are mode spot size, refractive index of the fluid, molar concentration of the species contained in the analyte, width of the fluidic gap, and waveguide geometry. By correlating various parameters, an optimal fluidic gap distance corresponding to a particular mode spot size that achieves the best sensitivity is determined both for refractive index and absorbance-based sensing.

IGF-1 stimulated upregulation of cyclin D1 is mediated via STAT5 signaling pathway in neuronal cells

Signal Transducer and Activator of Transcription (STATs) regulate various target genes such as cyclin D1, MYC, and BCL2 in nonneuronal cells which contribute towards progression as well as prevention of apoptosis and are involved in differentiation and cell survival. However, in neuronal cells, the role of STATs in the activation and regulation of these target genes and their signaling pathways are still not well established. In this study, a robust cyclin D1 expression was observed following IGF-1 stimulation in SY5Y cells as well as neurospheres. JAK/STAT pathway was shown to be involved in this upregulation. A detailed promoter analysis revealed that the specific STAT involved was STAT5, which acted as a positive regulatory element for cyclin D1 expression. Overexpression studies confirmed increase in cyclin D1 expression in response to STAT5a and STAT5b constructs when compared to dominant-negative STAT5. siRNA targeting STAT5, diminished the cyclin D1 expression, further confirming that STAT5 specifically regulated cyclin D1 in neuronal cells. Together, these findings shed new light on the mechanism of IGF-1 mediated upregulation of cyclin D1 expression in neural cell lines as well as in neural stem cells via the JAK/STAT5 signaling cascade.

EQCM investigation of electrochemical deposition and stability of Co-Pi oxygen evolution catalyst of solar energy storage

Photoassisted electrolysis of water is considered as an effective way of storing solar energy in the form of hydrogen fuel. This overall reaction involves the oxidation of water to oxygen at the anode and the reduction of protons to hydrogen at the cathode. Cobalt-phosphate-based catalyst (Co-Pi) is a potentially useful material for oxygen evolution reaction. In the present study, electrochemical deposition of Co-Pi catalyst is carried out on Au-coated quartz crystal from 0.1 M phosphate buffer (pH 7) containing 0.5 mM Co2+ ion, along with the simultaneous measurement of mass changes at the electrode surface. Cyclic voltammograms and mass variations are recorded during the course of deposition. A current peak is observed at 0.92 V vs Ag/AgCl, 3 M KCl corresponding to oxidation of Co2+ ion. The mass of the electrode starts increasing at this potential, suggesting the deposition of a Co(III)-based insoluble product on the electrode surface. The stability of the catalyst is also studied at several potentials in both buffered and nonbuffered electrolyte by monitoring the real-time mass variations.

Morphology dependent oxygen reduction activity of titanium carbide: bulk vs. nanowires

Titanium carbide (TiC) possesses fascinating properties like high electrical conductivity and high mechanical strength coupled with high corrosion resistance and stability in acidic and alkaline environments. The present study demonstrates the tunability of mechanistic aspects of oxygen reduction reaction (ORR) using TiC nanostructures. One dimensional TiC nanostructures (TiC-NW) have been synthesized using a simple, hydrothermal method and used as a catalyst for ORR. Shape dependent electroactivity is demonstrated by comparing the activity of TiC-NW with its bulk counterparts. Comparative studies reveal higher ORR activities in the case of 1D TiC-NW involving similar to 4 electrons showing efficient reduction of molecular oxygen. Excellent stability and high methanol tolerance with good selectivity for ORR is reported.

miR-219-5p inhibits receptor tyrosine kinase pathway by targeting EGFR in glioblastoma

Glioblastoma is one of the common types of primary brain tumors with a median survival of 12-15 months. The receptor tyrosine kinase (RTK) pathway is known to be deregulated in 88% of the patients with glioblastoma. 45% of GBM patients show amplifications and activating mutations in EGFR gene leading to the upregulation of the pathway. In the present study, we demonstrate that a brain specific miRNA, miR-219-5p, repressed EGFR by directly binding to its 3'-UTR. The expression of miR-219-5p was downregulated in glioblastoma and the overexpression of miR-219-5p in glioma cell lines inhibited the proliferation, anchorage independent growth and migration. In addition, miR-219-5p inhibited MAPK and PI3K pathways in glioma cell lines in concordance with its ability to target EGFR. The inhibitory effect of miR-219-5p on MAPK and PI3K pathways and glioma cell migration could be rescued by the overexpression of wild type EGFR and vIII mutant of EGFR (both lacking 3'-UTR and thus being insensitive to miR-219-5p) suggesting that the inhibitory effects of miR-219-5p were indeed because of its ability to target EGFR. We also found significant negative correlation between miR-219-5p levels and total as well as phosphorylated forms of EGFR in glioblastoma patient samples. This indicated that the downregulation of miR-219-5p in glioblastoma patients contribute to the increased activity of the RTK pathway by the upregulation of EGFR. Thus, we have identified and characterized miR-219-5p as the RTK regulating novel tumor suppressor miRNA in glioblastoma.

Fourteen gene GBM prognostic signature identifies association of immune response pathway and mesenchymal subtype with high risk group

Background: Recent research on glioblastoma (GBM) has focused on deducing gene signatures predicting prognosis. The present study evaluated the mRNA expression of selected genes and correlated with outcome to arrive at a prognostic gene signature. Methods: Patients with GBM (n = 123) were prospectively recruited, treated with a uniform protocol and followed up. Expression of 175 genes in GBM tissue was determined using qRT-PCR. A supervised principal component analysis followed by derivation of gene signature was performed. Independent validation of the signature was done using TCGA data. Gene Ontology and KEGG pathway analysis was carried out among patients from TCGA cohort. Results: A 14 gene signature was identified that predicted outcome in GBM. A weighted gene (WG) score was found to be an independent predictor of survival in multivariate analysis in the present cohort (HR = 2.507; B = 0.919; p < 0.001) and in TCGA cohort. Risk stratification by standardized WG score classified patients into low and high risk predicting survival both in our cohort (p = <0.001) and TCGA cohort (p = 0.001). Pathway analysis using the most differentially regulated genes (n = 76) between the low and high risk groups revealed association of activated inflammatory/immune response pathways and mesenchymal subtype in the high risk group. Conclusion: We have identified a 14 gene expression signature that can predict survival in GBM patients. A network analysis revealed activation of inflammatory response pathway specifically in high risk group. These findings may have implications in understanding of gliomagenesis, development of targeted therapies and selection of high risk cancer patients for alternate adjuvant therapies.